Running head: RANDOM NUMBER GENERATION 1
Random Number Generation: Types and Techniques
David DiCarlo
A Senior Thesis submitted in partial fulfillment
of the requirements for graduation
in the Honors Program
Liberty University
Spring 2012
RANDOM NUMBER GENERATION 2
Acceptance of Senior Honors Thesis
This Senior Honors Thesis is accepted in partial
fulfillment of the requirements for graduation from the
Honors Program of Liberty University.
______________________________
Mark Shaneck, Ph.D.
Chairman of Thesis
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Terry Metzgar, Ph.D.
Committee Member
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Monty Kester, Ed.D.
Committee Member
______________________________
James Nutter, D.A.
Honors Program Director
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Date
RANDOM NUMBER GENERATION 3
Abstract
What does it mean to have random numbers? Without understanding where a group of
numbers came from, it is impossible to know if they were randomly generated. However,
common sense claims that if the process to generate these numbers is truly understood,
then the numbers could not be random. Methods that are able to let their internal
workings be known without sacrificing random results are what this paper sets out to
describe. Beginning with a study of what it really means for something to be random, this
paper dives into the topic of random number generators and summarizes the key areas. It
covers the two main groups of generators, true-random and pseudo-random, and gives
practical examples of both. To make the information more applicable, real life examples
of currently used and currently available generators are provided as well. Knowing the
how and why of a number sequence without knowing the values that will come is
possible, and this thesis explains how it is accomplished.
RANDOM NUMBER GENERATION 4
Random Number Generation: Types and Techniques
A degree of randomness is built into the fabric of reality. It is impossible to say
for certain what a baby’s personality will be, how the temperature will fluctuate next
week, or which way dice will land on their next roll. A planet in which everything could
be predicted would be bland, and much of the excitement of life would be lost. Because
randomness is so inherent in everyday life, many researchers have tried to either harvest
or simulate its effect inside the digital realm. Before accomplishing this feat, however,
many important questions need to be answered. What does it mean to be random? How
does a person go about creating randomness, and how can he capture the randomness he
encounters? How can someone know if an event or number sequence is random or not?
Over generations, the answers to these questions have progressively been developed. This
paper takes a look at the current solutions, and attempts to organize the methods for
creating chaos.